Robust reader for CSV files exported by French versions of spreadsheet
software: ; separator, possible , decimal mark, several missing-value
codes, automatic encoding detection (UTF-8 or Latin-1 / Windows-1252).
Character columns that are actually numeric (e.g. "12,5") are converted.
Usage
read_cohort_csv(
path,
sep = ";",
na = c("", "NA", "NaN", ".", "NR", "ND"),
convert_comma_decimal = TRUE,
encoding = "auto",
...
)Arguments
- path
Path to the file (accents resolved with
path_resolve_nfc()).- sep
Field separator.
- na
Strings read as missing values.
- convert_comma_decimal
Convert character columns whose every non-missing value is a number written with a comma or a point.
- encoding
"auto"(UTF-8 if the file is valid UTF-8,"latin1"otherwise) or an explicit file encoding.- ...
Passed to
utils::read.csv().
Value
A data frame (column names unchanged, see clean_colnames()).
Examples
f <- system.file("extdata", "cohort_messy.csv", package = "vernissage")
raw <- read_cohort_csv(f)
#> Detected encoding: "latin1".
str(raw)
#> 'data.frame': 6 obs. of 8 variables:
#> $ Numéro patient: chr "P001" "P002" "P003" "P004" ...
#> $ Groupe : chr "Placebo" "Actif" "Placebo" "Actif" ...
#> $ Sexe : chr "F" "M" "M" "F" ...
#> $ Âge : int 64 71 58 66 73 61
#> $ NfL V0 : num 12.4 18.9 9.7 NA 21.3 11
#> $ NfL V3 : num 13.1 NA 10.2 14.8 22.6 11.5
#> $ Score MoCA V0 : int 27 24 29 26 NA 28
#> $ Commentaire : chr "RAS" "prélèvement hémolysé" NA NA ...